Paola Galozzi

Objectives: Pancreatic cystic neoplasms (PCNs), particularly intraductal papillary mucinous neoplasms (IPMNs), present a challenge for their potential malignancy. Despite promising biomarkers like CEA, amylase, and glucose, our study investigates whether metabolic indices in blood and cystic fluids (CFs), in addition to lymphocyte subsets and hematopoietic stem/progenitor cells (HSPCs), can effectively differentiate between high- and low-risk PCNs. Materials and Methods: A total of 26 patients (11 males, mean age 69.5 ± 9 years) undergoing Endoscopic Ultrasound-guided Fine Needle Aspiration were consecutively enrolled. Analyses included blood, serum, and CF, assessing glucose, CEA, cholesterol (total, HDL, and LDL), and total proteins. Flow cytometry examined immunophenotyping in peripheral blood and cystic fluids. Mass spectrometry was used for the metabolomic analysis of CF. Sensitivity, specificity, and ROC analyses evaluated discriminatory power. Results: A total of 25 out of 26 patients had IPMN. Patients were categorized as low or high risk based on multidisciplinary evaluation of clinical, radiological, and endoscopic data. High-risk patients showed lower CF total proteins and LDL cholesterol (p = 0.005 and p = 0.031), with a marked reduction in CF lymphocytes (p = 0.005). HSCPs were absent in CF. In blood, high-risk patients showed increased non-MHC-restricted cytotoxic T cells (p = 0.019). The metabolomic analysis revealed significantly reduced middle and long-chain acyl carnitines (AcCa) and tryptophan metabolites in high-risk patients. ROC curves indicated comparable discriminant abilities for CF lymphocytes (AUC 0.868), CF total proteins (AUC 0.859), and CF LDL cholesterol (AUC 0.795). The highest performance was achieved by the AcCa 14:2 and 16:0 (AUC: 0.9221 and 0.8857, respectively). Conclusions: CF levels of glucose, CEA, LDL cholesterol, and total proteins together with lymphocyte counts are easy translational biomarkers that may support risk stratification of PCNs in IPMN patients and might be endorsed by metabolomic analysis. Further studies are required for potential clinical integration.

As proponents of sustainable development within the health sector, we deem it necessary to highlight the critical importance of fostering multidisciplinary collaboration to address the urgent environmental and societal challenges facing healthcare today. The conventional silos in healthcare-encompassing medicine, nursing, and pharmacy-while effective in their respective domains, are insufficient when confronted with the complexities of sustainability [1]. The specialization of medicine has often placed professionals in a gilded isolation, characterized by solid certainties yet, at times, blind to the genuine needs of the broader context, which now demands a more integrated and comprehensive approach [2]. The integration of various disciplines, such as environmental science, engineering, economics, and social sciences, is not merely advantageous but necessary for tackling the intricate challenges of planetary health [3]. This need is increasingly being acknowledged and prioritized by funders, researchers, and even policymakers, who are advocating for enhanced multidisciplinary collaboration [4]. Healthcare significantly influences the global economy, influencing and being influenced by the broader environmental and socioeconomic landscape. The sector is both a heavy consumer of resources and a substantial generator of waste, making its impact on the environment substantial. Hospitals, for instance, consume energy at a rate approximately 2.75 times higher than other types of commercial buildings, due to their extensive ventilation, heating, cooling, and lighting needs, essential for maintaining optimal conditions for patient care [5]. Clinical laboratories further contribute to this footprint, consuming 3 to 6 times more energy per unit surface area compared to an office building [6]. With medical waste volumes escalating globally, it is estimated that healthcare-related waste comprises about 1-2% of total produced urban waste [7]. Considering those environmental stressors, together with greenhouse gases, particulate matter, air pollutants, and water use, it has been established that the global healthcare sector had a climate footprint of 2.0 Gt CO2e in 2014, equivalent to 4.4% of global net emissions [8]. If healthcare were a country, it would be the fifth-largest emitter on the planet, whose highest contributions come from the United States (546 Mt CO2e), China (342 Mt CO2e), and the European Union (248 Mt CO2e) [8]. This stark statistic is a call to action for incorporating sustainable practices that can drastically reduce such impacts. Multidisciplinary collaboration in sustainable healthcare significantly enhances the effectiveness and efficiency of healthcare systems while addressing complex environmental and social challenges. This approach integrates diverse expertise from fields such as environmental science, engineering, economics, and social sciences, which is essential for developing

Objective: Salivary alpha-amylase (sAA) has been recently proposed as biomarker of stress responsiveness within the sympathetic nervous system, preferable to cortisol, since limitations related to cortisol measurement (e.g. diurnal and seasonal rhythms, drugs interferences). Several factors, as age, collection device and analytical methods, also influence sAA levels and interpretation. This study aims to assess whether sAA could be useful to evaluate the stress response, also verifying some sources of variability. Methods: To identify any sources of sAA variability, saliva samples were collected from eight healthy subjects at five different times (8:00, 10:00, 12:00, 14:00 and 16:00) over five consecutive days using two different collection devices. Saliva was then collected from 35 obstetric residents before and after a simulated shoulder dystocia scenario, one of the most traumatic birth events in the professional life of gynecologists, to assess the stress levels. Samples were analysed throughout two different assays. Heart rate (HR) of residents was also measured before and after simulation scenario. Residents self-collected two saliva samples 10 min apart on a typical day. Results: Overall, sAA levels increased significantly from morning to afternoon. Levels varied between subjects, but no differences were found between days or sampling devices. sAA activity levels in samples from 35 residents were significantly higher than those obtained before the scenario took place (about ten minutes later). These results were confirmed by two different assays. Moreover, a similar trend was observed when HR was considered. No differences were observed between samples collected 10 minutes apart on a typical day. Conclusions: Salivary alpha-amylase activity is a reliable, quick, and efficient marker for stress response, then its measurement will be of potential interest in the field of stress-related disorders. However, it is important to consider the timing of sample collection before introducing sAA in a clinical setting.

Blau syndrome (BS) is a rare autoinflammatory granulomatosis characterized by granulomatous arthritis, uveitis, and dermatitis. Ocular complications are particularly severe in BS, significantly contributing to morbidity. This study aims to identify potential biomarkers for BS ocular degeneration through proteomic profiling of tear samples from affected patients. Seven subjects from the same family, including four carriers of the BS-associated NOD2 mutation (p.E383K), were recruited alongside healthy controls. Tear samples were collected using Schirmer strips and analyzed via mass spectrometry. A total of 387 proteins were identified, with significant differences in protein expression between BS patients, healthy familial subjects, and healthy controls. Key findings include the overexpression of alpha-2-macroglobulin (A2M) and immunoglobulin heavy constant gamma 4 (IGHG4) in BS patients. Bioinformatic analysis revealed that differentially expressed proteins are involved in acute-phase response, extracellular exosome formation, and protein binding. Notably, neutrophils’ azurophilic granule components, as azurocidin (AZU1), myeloperoxidases (MPO), and defensins (DEFA3), were highly expressed in the most severely affected subject, suggesting a potential role of neutrophils in BS ocular severity. These proteins might be promising biomarkers for ocular involvement in BS, facilitating early detection and tailored treatment strategies.

Objectives: Establishing direct reference intervals (RIs) for paediatric patients is a very challenging endeavour. Indirect RIs can address this problem, using existing clinical laboratory databases from real‐world data research. Compared to the traditional direct method, the indirect approach is highly practical, widely applicable, and low‐cost. Considering the relevance of dyslipidemia in the paediatric age, to provide better laboratory services to the local paediatric population, we established population‐specific lipid RIs via data mining.Methods: Our laboratory information system was searched for cholesterol (TC), triglycerides (TG), low‐density lipoprotein (LDL) and high‐density lipoprotein (HDL) of patients aged less than 18 years, performed from January 2009 until December 2022. RIs were estimated using RefineR algorithm.Results: Values from 215,594 patients were initially collected. After refining data on the basis of specific exclusion criteria that left 17,933 patients, we determined the RIs for each analyte, including corresponding 95% confidence interval (95% CI). Age and sex partitions were required for proper stratification of the heterogenous subpopulations. Age‐related variations in TC and TG values were observed mainly in children until 5 years. RIs were defined for children less than 3 years and for those of 3–18 years. In our population, the obtained RIs were comparable with those of the literature, but the upper TG limit in subjects under the age of 3 (2.03 mmol/L with 95% CI: 1.45–2.86) was lower than that previously reported.Conclusions: Our RIs, necessary for paediatric lipid monitoring, are tailored to the serviced patient population as should be done whenever possible.

Background: We compared the performance of 21 different assays performed by the Wantai Wan200+ (Wantai BioPharm, Beijing, China) with respect to other methods in use at the University Hospital of Padova (AOPD), Italy. Methods: The plasma (P) or serum (S) of 5027 leftover samples, collected from May to Sept 2023, was either analyzed or frozen at −20 °C. Beckman DXI800 (DXI), Roche Cobas 8000 e801 (RC), Snibe Maglumi 4000 plus (SM), DiaSorin Liaison XL (DL) and Binding Site Optilite (BS) equipment were used at the AOPD. P-procalcitonin (PCT), DXI; P-Troponin I (TnI), DXI; S-CA125, DXI; S-free PSA (f-PSA), DXI; S-total PSA (t-PSA), DXI; S-IL6, SM; P-Troponin T (TnT), RC; P-NT-proBNP, RC; P-Neuron-Specific Enolase (NSE), RC; S-CA15-3, DL; S-CA19-9, DL; S-AFP, DL; and S-CEA, DL were tested in fresh samples. P-Myoglobin (Myo), DXI; P-Cyfra21-1, RC; S-β2 microglobulin (B2MIC), BS; S-HE4, SM; S-PGI, SM; S-PGII, SM; S-CA72-4, SM; and S-CA50, SM were analyzed in frozen and thawed samples. Bland–Altman (BA), Passing–Bablok (PB) and Cohen’s Kappa (CKa) metrics were used as statistics. Results: An excellent comparability profile was found for 11 analytes. For example, the t-PSA CKa was 0.94 (95%CI: 0.90 to 0.98), and the PB slope and intercept were 1.02 (95%CI: 0.99 to 1.03) and 0.02 (95%CI: 0.01 to 0.03), respectively; the BA bias was 2.25 (95%CI: −0.43 to 4.93). Ten tested measurands demonstrated a suboptimal comparability profile. Biological variation in EFLM (EuBIVAS) performance specifications was evaluated to assess the clinical relevance of measured biases. Conclusions: Evaluation of the Wantai Wan200+’s performance suggests that between-method differences did not exceed the calculated bias. Metrological traceability may influence the comparisons obtained for some measurands.

The purpose of the study was to evaluate the antibody response after COVID-19 vaccination in patients affected by systemic autoinflammatory diseases (SAID) undertaking IL-1 inhibitors (IL-1i) compared to healthy vaccinated controls (HC). The course of COVID-19 in vaccinated patients on IL-1i was also assessed. The serological response was evaluated in SAID patients using the CLIA MAGLUMI TM 2000 Plus test after the first vaccination cycle and the booster dose. Fifty-four fully vaccinated healthcare workers were enrolled as HCs. GraphPad Prism 8 software was used for statistical analysis. All patients developed an adequate antibody response. No differences were observed between the antibody titers of patients on IL-1i and those not on IL-1i, either after the first vaccination cycle or the booster dose (p = 0.99), and to HC (p = 0.99). With increasing age, a decrease in antibody production was assessed after the second vaccine in SAID (r = 0.67, p = 0.0003). In general, 11.6% of SAID patients had COVID-19 after receiving vaccination. None of them developed severe disease or experienced flares of their autoinflammatory disease. In conclusion, patients receiving IL-1i develop an antibody response comparable to HC. No side effects after vaccination were observed; IL-1i was continued before and after injections to avoid flare-ups.